An active learning algorithm for linear systems attains the minimal sample complexity for accurate identification using ordinary least squares and semidefinite programming with centered excitation.
Hidden convexity in active learning: A convexified o nline input design for ARX systems
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Optimal Centered Active Excitation in Linear System Identification
An active learning algorithm for linear systems attains the minimal sample complexity for accurate identification using ordinary least squares and semidefinite programming with centered excitation.